TechGist05

Ever since machine translation was introduced into the professional translation industry, there have been questions about what the impact would be on a final delivered translation service product. For much of the history of MT many translators claimed that while translation production work using a post-edited MT (PEMT) process was faster, the final product was not as good. The research suggests that this has been true from a strictly linguistic perspective, but many of us also know that PEMT worked quite successfully with technical content especially with terminology and consistency even in the days of SMT and RBMT.  As NMT systems proliferate, we are at a turning point, and I suspect that we will see many more NMT systems that are in fact seen as providing useful output that clearly enhances translator productivity, especially on output from systems built by experts. NMT will also quite likely have an influence on the output quality and the difference is also likely to become less...

We live in an era where the issue of digital transformation is increasingly recognized as a primary concern, and a key focus of executive management teams in global enterprises. The stakes are high for businesses that fail to embrace change. Since 2000, almost half (52%) of Fortune 500 companies have either gone bankrupt, been acquired, or ceased to exist as a result of digital disruption. It’s also estimated that 75% of today’s S&P 500 will be replaced by 2027, according to Innosight Research.  Responding effectively to the realities of the digital world have now become a matter of survival as well a means to build long term competitive advantage. When we consider what is needed to drive digital transformation in addition to structural integration, we see that large volumes of current, relevant, and accurate content that support the buyer and customer journey are critical to enhancing the digital experience both in B2C and B2B scenarios.  Large volumes of relevant conte...

This is a guest post by the principals of Tmxmall, which is a Chinese Translation Memory Marketplace, i.e. a site that sells translation memory to interested parties (mostly translators and LSPs). This is one of two such intiatives coming from China. I will be featuring the other one shortly. Data is a critical requirement for any of the modern MT technology paradigms. While SMT was able to handle some level of noise  in the data used, it appears that NMT is more particular and the "more data is better" principal does not apply as clearly, if it ever did. The quality of the training data matters with AI and machine learning.  The pursuit of building up training data resources will always exist in the context of any Machine Learning technology. However, commodity data that you can easily obtain or buy tends to usually be low quality data, and not high-quality data by most people's assessment. This is what TAUS has to say about these new initiatives: "The internet gian...